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Approaches to Measuring Population Health Ian McDowell March, 2010


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Title: Approaches to Measuring Population Health Ian McDowell March, 2010

Approaches to Measuring Population Health Ian
McDowell March, 2010
  1. Mortality-based summary measures
  2. Combined disability mortality methods
  3. Conceptual rationale for summary measures
  4. Environmental indicators
  5. Global indicators

EPI 5343
1. Why do we need measures of population health?
  • Governments wish to monitor health of citizens
  • To set priorities for health services policies
  • To evaluate social and health policies
  • To compare health of different regions
  • To identify pressing health needs
  • To draw attention to inequalities in health
  • Highlight balance between length and quality of
  • Numerical index desirable a GNP of Health

Classifying Population Health Measures by their
  • Measures that describe current state
  • Health or disability status (e.g., surveys)
  • Evaluative measures (e.g., to assess outcomes of
    health policies)
  • Analytic measures include an implicit time
  • Predictive methods look forwards (risk
    assessment projections of disease burden)
  • Explanatory measures (income inequality or social
    cohesion) look backwards.

These purposes may correspond to different types
of research (shown in the ellipses)
Note this figure shows the typical blend of
methods you might use in a particular type of
study HSR would use descriptive and evaluative,
for example.
Classifying population health measures by their
  • Aggregate measures combine data from individual
    people, summarized at regional or national
    levels. E.g., rates of smoking or lung cancer.
  • Environmental health indicators record physical
    or social characteristics of the place in which
    people live and cover factors external to the
    individual, such as air or water quality, or the
    number of community associations that exist in a
    neighborhood. These can have analogues at the
    individual level.
  • Global health indicators have no obvious
    individual analogue. Examples include contextual
    indicators such as the existence of healthy
    public policy laws restricting smoking in public
    places, or social equity in access to care
    social cohesion, etc.
  • Morgenstern H. Ecologic studies in epidemiology
    concepts, principles, and methods. Annual
    Reviews of Public Health 1995 1661-81.

Linking the focus of a measure to its application
  • Aggregate measures are typically used in
    descriptive studies they focus on the
    individuals within the population, i.e.
    idiographic. They measure health in the
  • Environmental measures can be used in
    descriptive, analytic or explanatory studies
  • Global measures mainly used in analytic studies
    focus on generating theory (nomothetic studies).
    They could measure health of the population

Linking the target of a population intervention
to the type of measure Interventions can target
people, environmental factors, or policy in
These correspond to Morgensterns categories of
measures used to evaluate the intervention
and to the presumed etiological sequence
History of changing approaches to measuring
population health
  • Originally based on mortality rates. IMR is
    often used to describe level of development of a
  • With declining mortality, people with chronic
    disease survive morbidity disability gain
  • Concern with quality of life, not mere survival
  • To compare populations at different stages of
    economic development, it may be desirable to
    combine mortality and morbidity in a single,
    composite index

Aggregate Measures Mortality-Based Indicators
  • Life expectancy
  • Expected years of life lost
  • Potential years of life lost

Life Expectancy
  • Summary of all age-specific mortality rates
  • Estimates hypothetical length of life of a cohort
    born in a particular year
  • This assumes that current mortality rates will

Expectancies and Gaps
  • From a survival curve, we can either consider the
    life expectancy (E), or the gap (G) between
    current life expectancy and some ideal.
  • Expectancies are generic gaps can be
    disease-specific (e.g., life years lost due to

Classifying Health Gaps
  • Gap compare population health to some target
    Difference between time lived in health states
    less than ideal health and the target ideal
  • The implied norm or target can be arbitrary, but
    must be explicit and the same for all populations
    being compared. The precise value does not matter

Gap measures Expected Years of Life Lost
  • Compares individuals age of death to population
    life expectancy
  • Problems different countries may have different
    life expectancies
  • Its overall mortality, so cannot identify impact
    of a particular disease.
  • Standard Expected Years of Life Lost
  • Reference is to an ideal life expectancy
  • E.g., Japan (82 years for women)
  • Area between survivorship curve and the chosen

Potential Years of Life Lost (PYLL)
  • PYLL ( normal age at death actual age at
    death). Doesnt much matter what age is chosen
    as reference typically 75
  • Attempts to represent impact of a disease on the
    population death at a young age is a greater
    loss than death of an elderly person
  • Focuses attention on conditions that kill younger
    people (accidents cancers)
  • All-cause or cause-specific

3. Aggregate Measures that Combine Mortality
  • Health expectancies
  • Health gaps

Composite Measures
  • Broader representation of health of a population
  • Composite measures combine morbidity and
    mortality into a health index. (An index is a
    numerical summary of several indicators of
  • Mortality data typically derived from life
    tables morbidity indicators from health
    surveys, e.g.
  • Self-rated health
  • Disability or activity limitations
  • A generic health index

Point to Ponder
  • What types of individual measure can be
    meaningfully aggregated?
  • Can you make an index out of
  • Fingerprint patterns
  • Personality
  • Eye colour
  • Loneliness?

Sidebar Different Types of Morbidity Scales for
Use in Composite Measures
  • Generic instruments cover a wide range of health
    topics, e.g. reflecting the WHO definition.
    These can be health profiles (e.g., Sickness
    Impact Profile, SF-36) or health indexes
    (e.g., Health Utilities Index, EuroQol)
  • Specific instruments
  • Disease-specific (e.g., Arthritis Impact
    Measurement Scale)
  • Age-specific (e.g., Child Behavior Checklist)
  • Gender-specific (e.g., Womens Health

Survivorship Functions for Health States
This diagram extends the earlier one by
recognizing that not all survivors are perfectly
healthy. The lower area H shows the proportion
of people in good health (however defined) it
shows healthy life expectancy. The top curve
shows deaths intermediate area represents levels
of disability. Area G again represents the
health gap. The question arises whether the
people with a disability ought to be counted with
H or with G.
More details on the combined indicators
  • From the previous chart
  • We can still read from the bottom, and talk of
    health expectancies, or from the top, and
    create gap indexes years of life lost, etc.
  • The value of a life lived in less than perfect
    health is less than a healthy life-year. This
    leads to health-adjusted life expectancy
  • The indicators will fall in a descending
    sequence overall life expectancy, then
    health-adjusted life expectancy, then healthy
    life expectancy.

A Simple Presentation Life Expectancy and
Disability-Free Life Expectancy, Canada, 1986-1991
Life Expectancy from birth Disability-Free Life
Expectancy (DFLE)
1986 1991
Health expectancy measures
  • Generic term expected duration of life in
    various states of health.
  • Includes more specific terms such as
    Disability-Free Life Expectancy (DFLE)
  • Two main classes
  • Dichotomous rating healthy vs. unhealthy
  • Health state valuations for a range of levels

I. Dichotomous expectancies
  • Full health is rated 1 any state of poor health
    (mild, moderate, severe disability) is rated 0.
  • Average across a population.
  • This leads to Disability-free life expectancy
    (DFLE) weight of 1 for no disability and 0
    for all other states.
  • Expectation of life with no disability, or
    Healthy Life Expectancy (HLE).
  • Very sensitive to threshold chosen for defining

II. Polytomous states and valuations
  • These incorporate many levels of disability into
    life expectancy estimates, counting time spent in
    each level of disability.
  • Weights assigned to each disability level
    generally 0 to 1.0. These are multiplied by
    average time in each level and summed over
    different diseases.
  • Health-adjusted life expectancy (HALE)
  • Recent work uses utility weights, e.g. from
    Health Utilities Index, Quality of Well-Being
    Scale, EUROQoL, etc.

Polytomous Curves Showing Quality of Survival
The area H again includes healthy people -
although the definition may have changed. The
top curve shows deaths intermediate curves
represent three levels of disability. Each will
have a different severity weighting.
Health Expectancy by Income Level and Sex,
Canada, 1978 (Wilkins)
Severely disabled Restricted Minor
limitations Healthy
Conclusion Poor people not only die earlier, but
also experience more disability than
richer people.
Income Quintiles
Males Females
Relationship between Life Expectancy, Healthy
Life Expectancy, and Health-Adjusted Life
LE Life Expectancy
HALE Health-Adjusted Life Expectancy
HLE Healthy Life Expectancy (also
Health Expectancy)
By down-weighting the various levels of
disability, the HALE falls between LE and HLE
An alternative presentation
Death among these patients
Disease onset
  • Full Health Partial Health
    Premature mortality

Life expectancy
Disease (Stage and Severity)
Years of Life Lost due to premature
mortality (YLL)
Year Equivalents of life lost due to Reduced
Functioning (YERF)
Health Adjusted Life Years lost (YLL YERF)
Some HALE Results for Canada
  • Wolfson Wilkins at Statistics Canada used data
    from the National Population Health Survey to
    calculate HALEs, using the Health Utilities
    Index to weight different levels of imperfect
  • The difference between LE and HALE is 11 for
    men, and 15 for women, because women live longer
    and suffer more chronic disease at older ages
    (see the previous slide).
  • They recalculated HALEs, deleting certain types
    of disability, and found that sensory problems
    (eyesight, hearing) were the major contributor in
    Canada to lost years. Vision problems have a
    minor impact on health status, but are very
    common Pain was the second largest cause.
  • They also showed that less educated people both
    live shorter lives, and also experience more
  • Source Wolfson MC. Health Reports 19868(1)41-46

Gap Measures QALYs DALYs
  • Gap measures can also use a weighting for
    intermediate health states. This is necessary to
    combine time lost due to ill health with time
    lost due to premature mortality
  • Quality Adjusted Life Years (QALYs)
  • Can be expressed as lost (to disease) or gained
    (through an intervention)
  • Common outcome measurement in clinical trials,
    program evaluation, recording extra years of life
    provided by therapy the quality of that life
  • Typically use utility scale running from 0 to 1
  • DALYS (disability-adjusted life years) lost
    basically the same idea.

Standard Life Expectancy (SLE)
Standard Expected Years of Life Lost (SEYLL)
Health-Adjusted or Disability-Adjusted Life
Years lost (HALYs or DALYs)
Health gap measures
Mean Life Expectancy (LE)
Years Lived with Disability (YLD)
Health-Adjusted, or Disability-Adjusted Life
Expectancy (HALE or DALE)
Health expectancy measures
Healthy Life Expectancy (HLE), or
Disability-Free Life Expectancy (DFLE)
4. When do we Use Each Type of Measure?
  • Towards a Functional Classification

Recall our Classification of Measures
  • Descriptive measures
  • To record current health status
  • To evaluate change in health status
  • Analytic measures
  • Predictive methods that look forward
  • Explanatory measures that look backwards.

Characteristics of Descriptive Measures
  • Intuitively simple cover themes of interest to
    people in general (quality of life, etc)
  • Reflect values possible political influence
  • Time frame present
  • Emphasis on modifiable themes
  • Goal to make broad classifications

Characteristics of Evaluative Measures
  • Fine-grained select indicators that sample
    densely from relevant level of severity
  • Need to be sensitive to change produced by
    particular intervention
  • Content tailored to intervention usually not
  • Common emphasis on summary score
  • But should also cover potential side-effects

Match the Instrument to the Application
Population Monitoring
Outcomes Research
Patient Management
Source John Ware, October 2000
Characteristics of Predictive Measures
  • Content can be selective rather than
  • Items not necessarily modifiable, or even very
  • If derived from discriminant analysis, likely to
    be parsimonious
  • Focus on algorithmic scoring and interpretation
    (e.g., either x or y, plus z in the absence of w)

Characteristics of Explanatory Measures
  • Can combine various types of measures
    classifications, ranging from distal to proximal
  • Based on a conceptual model, rather than
    empirically based
  • There can therefore be rival explanatory
  • Content not necessarily modifiable factors, but
    these would be desirable

5. Environmental Measures
  • Compositional vs. Contextual Measures

  • Demographics age, ethnic composition, lone
    parents, dependency ratios, etc
  • Population resources wealth, educational levels,
  • Community social cohesion, watch programs,
    participation (voting, donations, etc)

  • Neighbourhood type, quality amenities,
  • Employment opportunities
  • Access to care
  • Environmental quality pollution levels air,
    water, noise
  • Climate
  • Equity

  • Some aggregated measures do not have a meaningful
    individual counterpart
  • Population density
  • Income inequality
  • unemployed
  • GNP
  • Some environmental variables have no individual
  • Air quality (SO2)
  • Road traffic density
  • Ambient temperature
  • Land use

6. Global Measures
  • Income inequalities,
  • Health inequalities.

Some examples of global measures
  • Social solidarity sense of identity artistic
    output public interest in health issues, etc.
  • Indicators of societal support the safety net
  • Quality of social institutions for health
    (health protection laws, etc.)
  • Social cohesion, neighbourhood quality, social

Canadian Social Health Index
Composite Indicator, including Homicides Alcohol-
related fatalities Affordable housing Income
equity Child poverty Child abuse IMR Teen
suicide Drug abuse High school drop-out
rate Unemployment Avg. weekly earnings Seniors
poverty rate Uninsured health costs for
Source Human Resources Development
Canada Applied Research Bulletin 199736-8
Measures of health distribution Health
  • Several possible indicators
  • Can be relative or absolute
  • They may choose different reference points and
    vary in whether they weight scores by population
  • The choice of summary measure of disparity
    affects the interpretation of changes in health

Indicators of Relative Disparities (1)
  • Rate Ratio (RR) - the ratio of the health status
    of the least healthy group to that of the most
    healthy. Value 1 if no disparity.
  • Index of Disparity (IDisp) - average difference
    between rates of disease in several groups and a
    reference rate, expressed as the proportion of
    the reference rate (i.e. a ratio). Commonly the
    best group rate is used as the reference since it
    represents the rate that all groups might aspire
    to. If no disparity, the index 0.
  • Relative Index of Inequality (RII) Ratio of
    morbidity or mortality rates between those at
    bottom of SES range to those at top. This is
    estimated using regression and corrects for other

Relative Disparities (2)
  • Relative Concentration Index (RCI) -  how much
    health or illness is concentrated among ranked
    social groups (e.g. educational levels, or
    wealth). Index weighted according to relative
    size of the groups. It takes on positive or
    negative values, showing direction of the
    relationship. Score 0 when no disparity.
  • Theil Index (TI) and Mean Log Deviation (MLD) -
    these summarize disproportionality between shares
    of health and shares of population, expressed as
    a ratio on a log scale, compared to overall rate
    in the population and weighted by group sizes.
    Log scale makes this index more sensitive to
    health differences further from the average than
    other measures. 
  • Note that using weighting as in RCI or Theil
    counts all individuals equally, while unweighted
    indices count all groups equally and weight
    individuals inversely with respect to the size of
    their social groups

Absolute Indicators of Disparities
  • Rate difference (RD) - simple arithmetic
    difference, typically between the lowest
    highest disease rates. Also known as the Slope
    Index of Inequality
  • Between-group variance (BGV) sum of squared
    deviations from a population average, weighted by
    group sizes. 
  • Absolute Concentration Index (ACI) - measures the
    extent to which health or illness is concentrated
    among particular social groups on the absolute
    scale, used with ordinally ranked social groups.
     Calculated as RCI x mean of the health variable.
    If no disparity, ACI 0. 
  • Index of Dissimilarity Absolute number or
    percentage of all cases that must be
    redistributed to obtain the same mortality rate
    for all SES groups.

Measure of Income Inequality Gini Coefficient
  • L(s) lies below line of equality when income
    inequality favours the rich
  • Gini coefficient is twice the area between the
    curve and the line of equality

Standardized Index of Health Inequality
  • L(s) lies above line of equality when ill-health
    is concentrated among poor.
  • L(s) is indirectly standardized curve indicating
    unavoidable inequality (e.g., due to age-sex
  • Inequality favours rich if L(s) lies above L(s)

Cum of ill-health
Cum. of population ordered by income
Achievement Index (Wagstaff, 2001)
Mean Under 5 Mortality Rate, and Achievement
Index for India and Bangladesh
  • This corrects the mean of any health indicator by
    the extent of distributional inequality.
  • Multiply mean by concentration index L(s) in
    previous slide.
  • E.g., in diagram at right, U5 mortality for India
    is lower than Bangladesh.
  • But in India mortality is concentrated among
    poorer people more than in Bangladesh
    concentration index is -0.169, compared to
    -0.084 for Bangladesh. So achievement index
    mean x 117 139.
  • Resulting achievement index is equal for the two

Source http//
Acute Multidimensional Poverty An Index for
Developing Countries
  • Sabina Alkire,  Oxford Poverty Human
    Development Initiative.
  • Multidimensional Poverty Index (MPI) for 104
    developing countries. It assesses the nature and
    intensity of poverty at the individual level in
    education, health outcomes, and standard of
  • The MPI captures direct failures in functionings
    that Amartya Sen argues should form the focus for
    describing poverty. It is used to target the
    poorest, track the Millennium Development Goals,
    and design policies that address the interlocking
    deprivations poor people experience.
  • 1,700 million people in the world live in acute
    poverty, a figure that is between the 1.25/day
    and 2/day poverty rates
  • MPI available at http//
  • Report available online PDF 133p. at

Measures of Impact of Interventions to Reduce
  • Population attributable risk The reduction in
    health gap that would occur if everyone
    experienced the rates in the highest
    socioeconomic group
  • Population attributable life lost index The
    absolute or proportional increase in life
    expectancy if everyone experienced the life
    expectancy of the highest SES group